4.7 Article

Lung Cancer in Patients with Chronic Obstructive Pulmonary Disease Development and Validation of the COPD Lung Cancer Screening Score

出版社

AMER THORACIC SOC
DOI: 10.1164/rccm.201407-1210OC

关键词

COPD; screening; lung cancer

资金

  1. Red Tematica de Investigacion Cooperativa en Cancer, Instituto de Salud Carlos III [RD12/0036/0062]
  2. Spanish Ministry of Economy and Competitiveness
  3. European Regional Development Fund Una manera de hacer Europa, Spanish Ministry of Health FIS Projects) [PI04/2404, PI07/0792, PI10/01652, PI11/01626]
  4. University of Pittsburgh Lung Cancer SPORE [NCI P50-CA90440, 1P50 HL084948]
  5. University of Pittsburgh Cancer Institute
  6. University of Pittsburgh Medical Center

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Rationale: Patients with chronic obstructive pulmonary disease (COPD) are at high risk for lung cancer (LC) and represent a potential target to improve the diagnostic yield of screening programs. Objectives: To develop a predictive score for LC risk for patients with COPD. Methods: The Pamplona International Early Lung Cancer Detection Program (P-IELCAP) and the Pittsburgh Lung Screening Study (PLuSS) databases were analyzed. Only patients with COPD on spirometry were included. By logistic regression we determined which factors were independently associated with LC in PLuSS and developed a COPD LC screening score (COPD-LUCSS) to be validated in P-IELCAP. Measurements and Main Results: By regression analysis, age greater than 60, body mass index less than 25 kg/m(2), pack-years history greater than 60, and emphysema presence were independently associated with LC diagnosis and integrated into the COPD-LUCSS, which ranges from 0 to 10 points. Two COPD-LUCSS risk categories were proposed: low risk (scores 0-6) and high risk (scores 7-10). In comparison with low-risk patients, in both cohorts LC risk increased 3.5-fold in the high-risk category. Conclusions: The COPD-LUCSS is a good predictor of LC risk in patients with COPD participating in LC screening programs. Validation in two different populations adds strength to the findings.

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